\vsssub
\subsubsection{~$S_{in} + S_{ds}$: Rogers et al. 2012 \& Zieger et al. 2015} \label{sec:ST6}
\vsssub

\opthead{ST6}{AUSWEX, Lake George}{A. Babanin, I. Young, M. Donelan, E. Rogers, S. Zieger, Q. Liu}

\noindent
This version implements observation-based physics for deep-water source/sink terms. These include wind input
source term, and sink terms due to negative wind input, whitecapping
dissipation and wave-turbulence interactions (swell dissipation).
The wind input and whitecapping dissipation source terms are based on
measurements taken at Lake George, Australia; wave-turbulence dissipation
on laboratory experiments and field observations of swell decay; negative
input on laboratory testing. Constraint is imposed on the total wind
energy input through the wind stress, known independently.

\paragraph{Wind input.} Apart from first direct field measurements
of the wind input under strong wind forcing,  the Lake George experiment
revealed a number of new physical features for wind-wave exchange,
previously not accounted for:
(i) full air-flow separation that leads to a relative reduction of
wind input for conditions of strong winds/steep waves;
(ii) dependence of the wave growth rate on wave steepness,
which signifies nonlinear behavior of the wind-input source function;
(iii) enhancement of input in the presence of wave breaking
\citep{art:Dea06,art:Bea07} (the last feature was not implemented in here).
Following \citet{art:RBW12}, this input source term is formulated as
\begin{eqnarray}
\cS_{in}(k,\theta) & = & \frac{\rho_a}{\rho_w}\, \sigma\,\gamma(k,\theta)\,N(k,\theta)  ,
\label{eq:ST601} \\ \gamma(k,\theta) &=& G\,\sqrt{B_n}\,W  ,
\label{eq:ST602} \\
G                &=& 2.8-\Bigl (1+\tanh (10\sqrt{B_n}W-11) \Bigr)  ,
\label{eq:ST603} \\
B_n              &=& A(k)\,N(k)\sigma\,k^3  ,
\label{eq:ST604} \\
W                &=& \left (\frac{U_s}{c}\,-\,1 \right )^2  .
\label{eq:ST605}
\end{eqnarray}

\noindent
In (\ref{eq:ST601})$-$(\ref{eq:ST605}) $\rho_a$ and $\rho_w$ are densities
of air and water, respectively, $U_s$ is the scaling wind speed, $c$ refers to
wave phase speed, $\sigma$ is radian frequency and $k$
is wavenumber. The spectral saturation (\ref{eq:ST604}), introduced
by \citet{art:Phi84}, is a spectral measure of steepness $ak$.  The
omni-directional action density is obtained by integration over all directions:
$N(k)=\int N(k,\theta)d\theta$.\linebreak
The inverse of the directional spectral narrowness $A(k)$ is defined as\linebreak
$A^{-1}(k) =$ $\int_{0}^{2\pi} [{N(k,\theta)}/{N_{\max}(k)}] d\theta$,
where $N_{\max}(k)=\max\bigl \{N(k,\theta)\bigr \}$, for all
directions $\theta\in[0,2\pi]$ \citep{art:BS87}.

\citet{art:Dea06} parameterized the growth rate (\ref{eq:ST602}) in terms
of winds 10\,m above the mean surface. Wave models, however, typically employ friction
velocity $u_\star=\tau/\rho_a$ to assure a consistent fetch law across
different wind speeds \citep[][p. 253]{bk:WAM94}. Therefore, \citet{art:RBW12}
advocated using an approximation
\begin{equation}
U_s = U_{10} \simeq \Upsilon u_{\ast},\ \mathrm{and}\ \Upsilon = 28
\label{eq:Upsilon}
\end{equation}
by following \citet{art:KHH84}.

\begin{eqnarray}
W_1 & = & \mathrm{max}^2 \left \{ 0,\frac{U}{c}\ \cos(\theta-\theta_w)-1
\right \}  , \label{eq:ST606-1} \\
W_2 & = & \mathrm{min}^2 \left \{ 0,\frac{U}{c}\ \cos(\theta-\theta_w)-1
\right \} .\label{eq:ST606-2}
\end{eqnarray}

\noindent
The directional distribution of $W$ is implemented as the sum of favorable
winds (\ref{eq:ST606-1}) and adverse winds (\ref{eq:ST606-2}), so that they
complement one another (i.e. $W=\{W_1\cup W_2$\}, see {\it Negative Input}
later this section):
\begin{equation}\label{eq:ST606}
W=W_1-a_0\,W_2  .
\end{equation}

\paragraph{Wind input constraint.} One important part of the input is the
calculation of the momentum flux from the atmosphere to the ocean,
which must agree with the flux received by the waves. At the surface,
the stress $\vec{\tau}$ can be written as the sum of the viscous and
wave-supported stress: $\vec{\tau} = \vec{\tau}_{v} + \vec{\tau}_{w}$.
The wave-supported stress $ \vec{\tau}_{w}$ is used as the principal
constraint for the wind input and cannot exceed the total stress
$\vec{\tau} \le \vec{\tau}_{tot}$.  Here the total stress is determined
by the flux parameterization: $\vec{\tau}_{tot}=\rho_a u_\star|u_\star|$.
The wave-supported stress $\tau_w$ can be calculated by integration over
the wind-momentum-input function:

\begin{equation}\label{eq:ST609}
   \vec{\tau}_w = \rho_w g \int_{0}^{2\pi} \int_{0}^{k_{max}}
   \frac{S_{in}(k^\prime,\theta)}{c} \Bigl (\cos\theta,\sin\theta \Bigr )
   dk^\prime d\theta  .
\end{equation}

\noindent
Computation of the wave-supported stress (\ref{eq:ST609}) includes the
resolved part of the spectrum up to the highest discrete wavenumber $k_{max}$,
as well as the stress supported by short waves. To account for the latter,
an $f^{-5}$ diagnostic tail is assumed beyond the highest frequency in the
energy density spectrum. In order to satisfy the constraint and in the case
of $\vec{\tau} > \vec{\tau}_{tot}$, a wavenumber dependent factor $L$ is
applied to reduce energy from the high frequency part of the spectrum:
$S_{in}(k^\prime)=L(k^\prime)\,S_{in}(k^\prime)$ with

\begin{equation}\label{eq:ST610}
L(k^\prime) = \min \Bigl \{ 1, \exp \bigl ( \mu\,[1- U/c] \bigr ) \Bigr
\}  .
\end{equation}

\noindent
The reduction (\ref{eq:ST610}) is a function of wind speed and phase speed and
follows an exponential form designed to reduce energy from the discrete part
of the spectrum. The strength of reduction is controlled by coefficient $\mu$,
which has a greater impact at high frequencies and only little impact on the
energy-dominant part of the spectrum. The value of $\mu$ is dynamically
calculated by iteration at each integration time step \citep{art:Tea10}.

The drag coefficient is given by
\begin{equation}\label{eq:ST607}
C_d \times 10^4 = 8.058 + 0.967 U_{10} - 0.016 U_{10}^2 ,
\end{equation}
which was selected and
implemented as switch {\code FLX4}. The parameterization was proposed by
\citet{art:Hwa11} and accounts for saturation, and further decline
for extreme winds, of the sea drag at wind speeds in excess of 30\,m~s$^{-1}$.
To prevent $u_\star$ from dropping to zero at very strong winds
($U_{10}\ge50.33$m~s$^{-1}$) expression (\ref{eq:ST607}) was modified to yield
$u_\star=2.026$m~s $^{-1}$. {\it Important!} In {\code ST6}, bulk adjustment to any
uniform bias in the wind input field is done in terms of the wind stress
parameter $u_\star$ rather than $U_{10}$. In order to achieve that, the
factor in expression $C_d \times 10^4$ on the left hand side of
(\ref{eq:ST607}) was substituted with $C_d \times \mathrm{FAC}$ and added
as the {\F FLX4} namelist parameter {\code CDFAC} (see {\it Bulk Adjustment}
at the end of this section).
The viscous drag coefficient,
\begin{equation}\label{eq:ST608}
  C_v \times 10^3 = 1.1 - 0.05 U_{10} ,
\end{equation}
was parameterized by \citet{art:Tea10} as a function of wind speed using
data from \citet{art:BP98}.

\paragraph{Negative Input.} Apart from the positive input, {\code ST6} also has a
negative input term in order to attenuate the growth of waves in those parts
of the wave spectrum where an adverse component of the wind stress is present
(\ref{eq:ST606-1}--\ref{eq:ST606-2}). The growth rate for adverse winds
is negative \citep{pro:Don99} and is applied after the constraint of
the wave-supported stress $\tau_w$ is met. The value of $a_0$
(in \ref{eq:ST606}) is a tuning parameter in the parameterization of the
input and is adjustable through the {\F SIN6} namelist parameter {\code  SINA0}.


\noindent
\paragraph{Whitecapping Dissipation.} For dissipation due to wave breaking,
the Lake George field study revealed a number of new features: (i) the
threshold behavior of wave breaking \citep{art:BBY01}. The waves do not
break unless they exceed a generic steepness in which case the wave breaking
probability depends on the level of excedence above this threshold steepness.
For waves below the critical threshold, whitecapping dissipation is zero.
(ii) the cumulative dissipative effect due to breaking and dissipation of
short waves affected by longer waves
\citep{pro:Don01,pro:BY05,art:Mea06,art:YB06,art:Bea10},
(iii) nonlinear dissipation function at strong winds
(\citeauthor{art:Mea06}, \citeyear{art:Mea06};\linebreak
 \citeauthor{art:Bea07}, \citeyear{art:Bea07}),
(iv) bimodal distribution of the directional spreading of the dissipation
\citep{art:YB06,art:Bea10} (the last feature was not implemented in {\code ST6}).
Following \citet{art:RBW12}, the whitecapping dissipation term is
implemented as:
\begin{equation}\label{eq:ST620}
  \cS_{ds}(k,\theta) = \Bigl [ T_1(k,\theta) + T_2(k,\theta) \Bigr ]\ N(k,\theta) ,
\end{equation}

\noindent
where $T_1$ is the inherent breaking term, expressed as the traditional function
of the wave spectrum, and $T_2$, expressed as an integral of the wave spectrum below
wavenumber $k$, accounts for the cumulative effect of short-wave breaking or
dissipation due to longer waves at each frequency/wavenumber. The inherent breaking
term $T_1$ is the only breaking-dissipation term if this frequency is at or below
the spectral peak. Once the peak moves below this particular frequency, $T_2$
becomes active and progressively more important as the peak downshifts further.

The threshold spectral density $F_{\mathrm{T}}$ is calculated as
\begin{equation}\label{eq:ST621}
  F_{\mathrm{T}}(k)=\frac{\varepsilon_{\mathrm{T}}}{A(k)\,k^3}  ,
\end{equation}
where $k$ is the wavenumber and with
$\varepsilon_{\mathrm{T}}=0.035^2$ being an empirical constant
\citep{art:Bea07,bk:Bab11}. Let the level of exceedence above the critical
threshold spectral density (at which stage wave breaking is predominant) be
defined as $\Delta(k)=F(k)-F_{\mathrm{T}}(k)$. Furthermore, let
$\mathcal{F}(k)$ be a generic spectral density used for normalization,
then the inherent breaking component can be calculated as
\begin{equation}\label{eq:ST622}
T_1(k)=a_1 A(k)\frac{\sigma}{2\pi} \left [ \frac{\Delta(k)}{\mathcal{F}(k)}
\right ]^{p_1}  .
\end{equation}

\noindent
The cumulative dissipation term is not local in frequency space and is
based on an integral that grows towards higher frequencies, dominating at
smaller scales:

\begin{equation}\label{eq:ST623}
T_2(k)=a_2 \int\limits_0^k A(k) \frac{c_g}{2\pi} \left [
\frac{\Delta(k)}{\mathcal{F}(k)} \right ]^{p_2}\!\!dk .
\end{equation}

\noindent
The dissipation terms (\ref{eq:ST622})$-$(\ref{eq:ST623}) depend on five
parameters: a generic spectral density $\mathcal{F}(k)$ used for
normalization, and four coefficients $a_1$, $a_2$, $p_1$, and $p_2$.  The
coefficients $p_1$ and $p_2$ control the strength of the normalized threshold
spectral density $\Delta(k)/\mathcal{F}(k)$ of the dissipation terms.
Namelist parameter {\code SDSET} changes between the spectral density
$F(k)$ and threshold spectral density $F_{\mathrm{T}}(k)$ for
normalization in (\ref{eq:ST622})--(\ref{eq:ST623}).
According to \citet{art:Bea07} and \citet{art:Bab09}, the directional
narrowness parameter is set to unity $A(k)\approx 1$ in Eqs.
(\ref{eq:ST621})$-$(\ref{eq:ST623}).

% -------------------------------------------------------------------
\begin{table} \begin{center}
\footnotesize
\begin{threeparttable}
\begin{tabular}{|l|c|c|c|c|c|} \hline \hline
Parameter          &  WWATCH var. & namelist &  vers.\,4.18 & vers.\,5.16 & vers.\,\WWver \\
\hline
  $F_{\mathrm{T}}$ &  SDSET       & SDS6     &  T       &  T         & T          \\
  $a_1$            &  SDSA1       & SDS6     & 6.24E-7  & 3.74E-7    & 4.75E-6    \\
  $p_1$            &  SDSP1       & SDS6     &  4       &  4         & 4          \\
  $a_2$            &  SDSA2       & SDS6     & 8.74E-6  & 5.24E-6    & 7.00E-5    \\
  $p_2$            &  SDSP2       & SDS6     &  4       &  4         & 4          \\
\hline
  $\Upsilon$\tnote{\textdagger}       &  SINWS       & SIN6     & n/a      & n/a        & 32.0       \\
  $N_{hf}$\tnote{\textdagger}         &  SINFC       & SIN6     & n/a      & n/a        & 6.0        \\
  $a_0$            &  SINA0       & SIN6     & 0.04     & 0.09       & 0.09       \\
  $b_1$ is constant&  CSTB1       & SWL6     & n/a      &  F         & F          \\
  $b_1$, $B_1$     &  SWLB1       & SWL6     & 0.25E-3  & 0.0032     & 0.0041     \\
  $\mathrm{FAC}$   &  CDFAC       & FLX4     & 1.00E-4  & 1.00E-4    & 1.0        \\
\hline
  $C$              &  NLPROP      & SNL1     & 3.00E7   &  3.00E7    & 3.00E7    \\
 \hline \hline
\end{tabular}
\begin{tablenotes}
	\item[\textdagger] In WW3 version 4.18 and 5.16, $\Upsilon = 28.0$
            and $N_{hf} = 6.0$ were hard-coded in {\code ST6} module.
\end{tablenotes}
\end{threeparttable} \end{center}
\caption{Summary of calibration parameters for {\code ST6} when it is applied with
         the {\code DIA} nonlinear solver (section~\ref{sec:NL1}). Values tabulated represent default model settings.
         Abbreviation ``n/a'' indicates that the variable is not applicable
         in that release of the code.}
\label{tab:ST601} \botline \end{table}
% -------------------------------------------------------------------

\citet{art:RBW12} calibrated the dissipation terms based on duration-limited
academic tests. Calibration coefficients used in {\code ST6} and listed in
Table~\ref{tab:ST601} differ somewhat from those of \citet{art:RBW12}
mainly due to the fact that the wave-supported stress $\vec{\tau}_w$
is implemented in the form of vector components and the non-breaking swell
dissipation (\ref{eq:ST624}) was previously not accounted for in
\citet{art:RBW12}.

\paragraph{Swell Dissipation.} In the absence of wave breaking,
other mechanisms of wave attenuation are present. Here, they are
referred to as swell dissipation and parameterized in terms of
the interaction of waves with oceanic turbulence \citep{bk:Bab11}.
This mechanism, however, remains active for the wind-generated
waves too. Its contribution across the spectrum is small, if the
spectrum is above the wave-breaking threshold, but it is dominant
at the front face of the spectrum, or even at the peak in case of
the full Pierson-Moscowitz development.

\begin{equation}\label{eq:ST624}
  \cS_{swl}(k,\theta) = -\frac{2}{3}b_1 \sigma\ \sqrt{B_n}\ N(k,\theta).
\end{equation}

\noindent
By making coefficient $b_1$ in Eq. (\ref{eq:ST624}) dependent
on steepness the large gradient in the spatial bias in wave height
can be reduced:

\begin{equation}\label{eq:ST625}
   b_1 = B_1 \, 2\sqrt{E}\,k_p .
\end{equation}

In Eq. (\ref{eq:ST625}), $B_1$ is a scaling coefficient,
$E$  is the total sea surface variance Eq. (\ref{eq:etot}) and $k_p$
is the peak wavenumber.  Eq. (\ref{eq:ST625}) can be
flagged through the {\F SWL6} namelist parameter {\code CSTB1}.The value for the
coefficient $B_1$ in Eq. (\ref{eq:ST625}) and/or $b_1$ in Eq. (\ref{eq:ST624})
is customizable through the {\F SWL6} namelist parameter {\code SWLB1}
(see Table~\ref{tab:ST601}).

\noindent
\paragraph{Updates since vers.\,\WWver} Following \citet{art:RBW12}, the
scaling wind speed $U_s = 28u_{\ast}$ (\ref{eq:Upsilon}) were adopted in
vers. 4.18 and vers. 5.16 (Table~\ref{tab:ST601}). Such configurations of {\code ST6} have been proven
skillful for different spatial scales and under different weather
conditions \citep[e.g.][]{art:ZBRY15, liu2017}. \citet[][their Fig. 5]{art:ZBRY15},
however, also suggested {\code ST6} (vers. 4.18 and vers. 5.16) was inclined to
overestimate the energy level of the high-frequency tail of the spectrum,
indicating an inaccurate balance of different source terms in this
specific frequency range.

Rogers (2014, unpublished work) found that using $U_s = 32u_{\ast}$ (i.e.,
$\Upsilon = 32$) could improve model skills in estimating tail level in
the {\code ST6} implementation in SWAN [see also \citet{Rogers2017}]. Following
this, \citet{Liu2019} carried out a thorough recalibration of {\code ST6} with WW3,
and the new set of parameters (i.e., $a_0,\ a_1,\ a_2,\ B_1$) is summarized
in the last column of Table~\ref{tab:ST601}. The updated {\code ST6} package not
only performs well in predicting commonly-used bulk wave parameters (e.g.,
significant wave height and wave period) but also yields a clearly-improved
estimation of high-frequency energy level (in terms of saturation spectrum
and mean square slope). In the duration-limited test, the omnidirectional
frequency spectrum $E(f)$ from the recalibrated {\code ST6} shows a clear transition
behavior from the power law of approximately $f^{-4}$ to the power law of
about $f^{-5}$, comparable to previous field studies \citep{Forristall1981}.

% -------------------------------------------------------------------
\begin{table}[htbp]
	\footnotesize
	\begin{center}
	\begin{tabular}{|l|c|c|c|c|} \hline \hline
            {\code ST6} & $a_0$ & $a_1$ & $a_2$ & $B_1$\\
                        & 0.05 & $4.75 \times 10^{-6}$ & $7.00 \times 10^{-5}$ & $6.00 \times 10^{-3}$  \\
            \hline
            {\code GMD} & $\lambda$ & $\mu$ & $\theta_{12}\ (^{\circ})$ & $C_{deep}$  \\
                        & $0.127$ & $0.000$ & $\ 3.0$ & $4.88 \times 10^7$            \\
		        & $0.127$ & $0.097$ & $21.0$ & $1.26 \times 10^8$             \\
		        & $0.233$ & $0.098$ & $26.5$ & $6.20 \times 10^7$             \\
		        & $0.283$ & $0.237$ & $24.7$ & $2.83 \times 10^7$             \\
		        & $0.355$ & $0.183$ & $-$ & $1.17 \times 10^7$                \\
            \hline \hline
	\end{tabular}
	\end{center}
        \caption{Summary of calibration parameters for {\code ST6} when it is applied with the {\code GMD} nonlinear solver (or specifically, {\code G35})}
	\label{tab:ST602}
	\botline
\end{table}
% -------------------------------------------------------------------

Apart from applying {\code ST6} with the {\code DIA} (section~\ref{sec:NL1}) nonlinear solver, \citet{Liu2019}
also made an attempt to run {\code ST6} with the {\code GMD} parameterization of $S_{nl}$
(section~\ref{sec:NL3}). As a first step, only the {\code GMD} configuration with
5 quadruplets and a three-parameter quadruplet definition
\citep[i.e., {\code G35} in][]{tol:OMOD13d} was adopted. The tunable parameters
of the {\code GMD} which were specifically optimized for {\code ST6} by using the holistic
genetic optimization technique designed by \citet{tol:OMOD13e}, and the
corresponding tunable parameters of {\code ST6} are summarized in
Table~\ref{tab:ST602}\footnote{For the fifth quadruplet layout of {\code GMD} shown
in Table~\ref{tab:ST602}, the three-parameter $(\lambda,\ \mu,\ \theta_{12})$
quadruplet definition degrades to a two-parameter $(\lambda,\ \mu)$ form, and
$\theta_{12}$ is implied by the value of $\mu$ \citep{tol:OMOD13d}. Accordingly,
a combination of {\code ST6+GMD} and the conservative nonlinear high-frequency
filter of \citet{tol:OMOD11} [see also section~\ref{sec:NLS}] might be
necessary to stabilize the model integration, particularly for high-resolution
spectral grid (say, $\Delta \theta < 5^{\circ}$).},\footnote{Unlike
Table~\ref{tab:ST601}, here we only show important parameters of {\code ST6} and
{\code GMD}. The reader is refered to {\code bin/README.UoM} for the detailed
set up of namelist variables for this specific model configuration.}.
\citet{Liu2019} demonstrated that in the duration-limited test, the
{\code GMD}-simulated $E(f)$ is in excellent agreement with that from the exact
 solutions of $S_{nl}$(e.g., {\code WRT}; section~\ref{sec:NL2}) \citep[see also][]{tol:OMOD13d}]. In a 1-yr global
hindcast, the {\code DIA}-based model overestimates the low-frequency wave energy
(wave period $T > 16$ s) by 90\%. Such model errors are reduced significantly
by the {\code GMD} to $\sim$20\%. It is noteworthy that the computational expense
of the {\code GMD} approach presented in Table~\ref{tab:ST602}, however, is about
5 times larger than that of the {\code DIA}.

To flexibly control the high-frequency extent of the prognostic frequency
region, we introduced
\begin{equation}
f_{hf} = N_{hf}/T_{m0, -1}
\end{equation}
in vers.\,\WWver, where $f_{hf}$ is the cut-off high-frequency limit
(\ref{eq:tail_E_f}), $T_{m0,-1}$ is the mean wave period defined in
(\ref{eq:Tm0m1}). $N_{hf}$ is set through a namelist parameter SINFC
(Table~\ref{tab:ST601}), and a negative $N_{hf}$ (say, $N_{hf} = -1$)
means \emph{the high-frequency spectral tail evolves freely without any
prescribed slope.}

\noindent
\paragraph{Dominant Wave Breaking Probability}
Following \citet[][their Fig.~12]{art:BBY01}, the dominant wave breaking probability $b_T$ can be estimated from the wave spectrum $F(f, \theta)$ according to the following parametric form
\begin{equation}
b_T = 85.1 \Big[ (\epsilon_p - 0.055) (1 + H_s / d) \Big]^{2.33},
\label{eq:bt}
\end{equation}
where $H_s$ is the significant wave height, $d$ is the water depth, $\epsilon_p$ is the significant steepness of the spectral peak, given by
\begin{equation}
%\left \lbrace
\begin{array}{rcl}
\epsilon_p &=& H_p k_p / 2\\
H_p &=& 4 \Big[\int_{0}^{2\pi} \int_{0.7f_p}^{1.3f_p} F(f, \theta) \mathrm{d}f \mathrm{d}\theta \Big]^{1/2}
\label{eq:steepness}
\end{array}
%\right.
\end{equation}
where $k_p$ and $f_p$ are the peak wavenumber and frequency, respectively. Note that only the contribution from wind seas is considered when we calculate $H_s$, $H_p$ and $f_p$ ($k_p$) from $F(f, \theta)$ (Eqs. \ref{eq:bt} and \ref{eq:steepness}). Following \citet{Janssen1989} and \citet{Bidlot2001}, we consider spectral components as wind seas when
\begin{equation}
\frac{c(k)}{U_{10} \cos (\theta - \theta_u)}  < \beta_w,
\label{eq:beta}
\end{equation}
where $c(k)$ is the phase velocity, $U_{10}$ is the wind speed at 10 m above the sea surface, $\theta_u$ is the wind direction and $\beta_w$ is the constant wind forcing parameter. We implemented $\beta_w$ as a tunable parameter (the {\F MISC} namelist parameter {\code BTBET}), and used $\beta_w=1.2$ by default.

\noindent
\paragraph{Bulk Adjustments.} The source term
{\code ST6} has been calibrated with flux parameterization {\code FLX4}.
Bulk adjustment to the wind filed can be achieved by re-scaling the drag
parameterization {\code FLX4} through the {\F FLX4} namelist parameter {\code
 CDFAC=1.0E-4}\footnote{This was changed to {\code CDFAC=1.0} since vers.\,\WWver\ as the magnitude $10^{-4}$ was hard-coded
in {\code FLX4} module. (Table~\ref{tab:ST601})}. This has a similar effect to tuning variable
$\beta_{max}$ in {\code ST4} source term package, equations
(\ref{eq:SinWAM4}) and (\ref{eq:tauhfint}), which is customizable
through namelist parameter {\code BETAMAX} (see section
\ref{sec:ST3}--\ref{sec:ST4}). \citet{pro:Aea11} and \citet{art:RA13}
listed different sets of values that allow us to adjust to different
wind fields. When optimizing the wave model, it is recommended to
only re-tune parameters $a_0$, $b_1$ and $\mathrm{FAC}$. Again, $\mathrm{FAC}$
can potentially eliminate a bias in the wind field, which typically changes
with the selection of the reanalysis product. This reduction was tested
for extreme wind conditions such as hurricanes \citep{art:ZBRY15}.  In
a global hindcast, the coefficient for the negative input can be used to tune
the bulk of the wave heights in scatter comparisons, whereas the scaling
coefficient for swell dissipation primarily affects large sea states.
When the discrete interaction approximation ({\code DIA}) is used to compute the four-wave
interaction, the default value for the proportionality constant changes to
$C=3.00\times10^7$.

\textrm{\textit{\underline{Limitations of the code:}}} For vers. 4.18 and
vers. 5.16, in cases where the minimum time step for the dynamical source term
integration is much smaller than the overall time step (i.e. less than
1/15th), the model becomes unstable. The issue has been solved since vers.\,\WWver.
